{"id":"W4281831542","doi":"10.2196/36244","title":"Exploring Urological Malignancies on Pinterest: Content Analysis","year":2022,"lang":"en","type":"article","venue":"JMIR Cancer","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Prostate cancer; Grading (engineering); Malignancy; Genitourinary system; Kidney cancer; Cancer; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003888493,0.0002865515,0.0003600545,0.009060537,0.0005569424,0.001291237,0.0004610726,0.0003032896,0.003979132],"category_scores_gemma":[0.01981863,0.0001751801,0.0005593779,0.005982182,0.0006467779,0.001791231,0.002545209,0.0003470441,0.0004856933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001667431,"about_ca_system_score_gemma":0.001550028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002903455,"about_ca_topic_score_gemma":0.005933822,"domain_scores_codex":[0.9979622,0.000823574,0.0003363445,0.0001912358,0.0005094436,0.0001772457],"domain_scores_gemma":[0.982809,0.01178757,0.002617042,0.0003633795,0.002036337,0.0003867132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005880127,0.0003324535,0.6683503,0.008809373,0.0002148584,0.0011516,0.08692313,0.0006659735,0.005019906,0.001233403,0.01203946,0.2146715],"study_design_scores_gemma":[0.00003341682,0.000311634,0.8853156,0.001926047,0.0002286851,0.0008645024,0.07862566,0.002414144,0.002462533,0.0006025687,0.0271413,0.00007386062],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9823668,0.0005599383,0.001627156,0.0002829238,0.00002274297,0.001792876,0.008322863,0.00006476213,0.004959967],"genre_scores_gemma":[0.9739352,0.001657608,0.01096117,0.0002481259,0.00006939753,0.003042217,0.007578184,0.00006101923,0.002447089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009060537,"threshold_uncertainty_score":0.02056456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6611409051432489,"score_gpt":0.4726731760215377,"score_spread":0.1884677291217112,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}